Manager, Data Scientist - SBB Marketing & Deposit Strategy

Capital One • McLean, VA

1d • $197,300 - $225,100

About The Position

Capital One’s Small Business Bank (SBB) Data Science team partners across the organization to improve the performance and impact of financial products, policies, and services for small-business customers. The team applies statistics, machine learning, and emerging AI technologies to support entrepreneurs and their long-term success.

The Manager, Data Scientist will work with data scientists, software engineers, and product managers to develop customer-focused products and use large volumes of numeric and textual data to uncover business insights. The role develops machine learning models through design, training, evaluation, validation, and implementation, and translates technical work into business goals. A key focus is building account-level lifetime value (NPV) models that forecast revenue and cost drivers to inform strategic decision-making across SBB.

The role uses technologies such as Python, Conda, AWS, H2O, and Spark. The ideal candidate is comfortable with open-source tools and cloud platforms, can retrieve and analyze data from varied sources and structures, and enjoys defining and solving ambiguous problems. They keep current with emerging technologies and state-of-the-art methods and look for opportunities to apply them.

Requirements

• Currently hold or be obtaining, with the required degree expected on or before the scheduled start date, a qualifying quantitative degree and relevant data analytics experience: a bachelor's degree plus 6 years; a master's degree or quantitatively concentrated MBA plus 4 years; or a PhD plus 1 year.
• At least 1 year of experience using open-source programming languages for large-scale data analysis.
• At least 1 year of experience working with machine learning.
• At least 1 year of experience utilizing relational databases.
• Hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
• Ability to retrieve, combine, and analyze data from a variety of sources and structures.

Nice To Haves

• PhD in a STEM field plus 3 years of experience in data analytics.
• At least 1 year of experience working with AWS.
• At least 4 years of experience using Python, Dask, Spark, or similar tools for large-scale data analysis.
• At least 4 years of experience with machine learning and statistical modeling.
• At least 4 years of experience with SQL.

Responsibilities

• Partner with data scientists, software engineers, and product managers to deliver products customers value.
• Use technologies including Python, Conda, AWS, H2O, and Spark to analyze large volumes of numeric and textual data and uncover insights.
• Develop machine learning models through design, training, evaluation, validation, and implementation.
• Translate technical work and its complexity into tangible business goals.
• Develop account-level lifetime value (NPV) models that forecast revenue and cost drivers to inform strategic decision-making across SBB.
• Research and evaluate emerging technologies, methods, and applications, and identify opportunities to apply them.

Benefits

• Comprehensive health, financial, and other benefits supporting total well-being; eligibility varies by employment status and management level.
• Eligible for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager